Lightweight-IDS: Reproducible Edge Intrusion Detection Framework

This software provides the reproducible implementation accompanying the publication:

C. Stolz, F. Li, and J. Zhang,
"Implementing Lightweight Intrusion Detection System on Resource Constrained Devices,"
2024 Cyber Awareness and Research Symposium (CARS),
Grand Forks, ND, USA, 2024, pp. 1–6.
doi: 10.1109/CARS61786.2024.10778716

The framework implements a lightweight hybrid intrusion detection system (IDS) designed for deployment on resource-constrained IoT devices such as the Raspberry Pi. The system integrates signature-based detection (Snort) with machine learning-based anomaly detection to improve detection coverage while maintaining computational efficiency.

If you use this software in academic work, please cite the above publication.